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. 2010 Feb;59(2):324-34.
doi: 10.1007/s00248-009-9580-2. Epub 2009 Sep 16.

Relationship of atmospheric pollution characterized by gas (NO2) and particles (PM10) to microbial communities living in bryophytes at three differently polluted sites (rural, urban, and industrial)

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Relationship of atmospheric pollution characterized by gas (NO2) and particles (PM10) to microbial communities living in bryophytes at three differently polluted sites (rural, urban, and industrial)

Caroline Meyer et al. Microb Ecol. 2010 Feb.

Abstract

Atmospheric pollution has become a major problem for modern societies owing to its fatal effects on both human health and ecosystems. We studied the relationships of nitrogen dioxide atmospheric pollution and metal trace elements contained in atmospheric particles which were accumulated in bryophytes to microbial communities of bryophytes at three differently polluted sites in France (rural, urban, and industrial) over an 8-month period. The analysis of bryophytes showed an accumulation of Cr and Fe at the rural site; Cr, Fe, Zn, Cu, Al, and Pb at the urban site; and Fe, Cr, Pb, Al, Sr, Cu, and Zn at the industrial site. During this study, the structure of the microbial communities which is characterized by biomasses of microbial groups evolved differently according to the site. Microalgae, bacteria, rotifers, and testate amoebae biomasses were significantly higher in the rural site. Cyanobacteria biomass was significantly higher at the industrial site. Fungal and ciliate biomasses were significantly higher at the urban and industrial sites for the winter period and higher at the rural site for the spring period. The redundancy analysis showed that the physico-chemical variables ([NO(2)], relative humidity, temperature, and site) and the trace elements which were accumulated in bryophytes ([Cu], [Sr], [Pb]) explained 69.3% of the variance in the microbial community data. Moreover, our results suggest that microbial communities are potential biomonitors of atmospheric pollution. Further research is needed to understand the causal relationship underlined by the observed patterns.

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